Physical Sciences and Mathematics Commons^™

A Mechanistically Guided Approach To Treatment Of Multi-Wavelet Reentry: Experiments In A Computational Model Of Cardiac Propagation, Richard T. Carrick

Graduate College Dissertations and Theses

Atrial fibrillation (AF) is the most common cardiac arrhythmia in the United States today. However, treatment options remain limited despite the enormous magnitude of both AF prevalence and the associated economic cost. Of those treatment options that are available, ablation-based interventional methods have demonstrated the highest rates of long-term cure. Unfortunately, these methods have substantially lower efficacy in patients with heavier burdens of disease, thus leaving the most affected individuals with the least hope for successful treatment.

The focus of this research is to develop a mechanistically guided approach towards the treatment of multi-wavelet reentry (MWR), one of the primary …

Evolving Spatially Aggregated Features For Regional Modeling And Its Application To Satellite Imagery, Sam Kriegman

Graduate College Dissertations and Theses

Satellite imagery and remote sensing provide explanatory variables at relatively high resolutions for modeling geospatial phenomena, yet regional summaries are often desirable for analysis and actionable insight. In this paper, we propose a novel method of inducing spatial aggregations as a component of the statistical learning process, yielding regional model features whose construction is driven by model prediction performance rather than prior assumptions. Our results demonstrate that Genetic Programming is particularly well suited to this type of feature construction because it can automatically synthesize appropriate aggregations, as well as better incorporate them into predictive models compared to other regression methods …

Modeling The Spatiotemporal Dynamics Of Cells In The Lung, Joshua Jeremy Pothen

Graduate College Dissertations and Theses

Multiple research problems related to the lung involve a need to take into account the spatiotemporal dynamics of the underlying component cells. Two such problems involve better understanding the nature of the allergic inflammatory response to explore what might cause chronic inflammatory diseases such as asthma, and determining the rules underlying stem cells used to engraft decellularized lung scaffolds in the hopes of growing new lungs for transplantation. For both problems, we model the systems computationally using agent-based modeling, a tool that enables us to capture these spatiotemporal dynamics by modeling any biological system as a collection of agents (cells) …

Enabling Machine Science Through Distributed Human Computing, Mark David Wagy

Graduate College Dissertations and Theses

Distributed human computing techniques have been shown to be effective ways of accessing the problem-solving capabilities of a large group of anonymous individuals over the World Wide Web. They have been successfully applied to such diverse domains as computer security, biology and astronomy. The success of distributed human computing in various domains suggests that it can be utilized for complex collaborative problem solving. Thus it could be used for "machine science": utilizing machines to facilitate the vetting of disparate human hypotheses for solving scientific and engineering problems.

In this thesis, we show that machine science is possible through distributed human …

A Hybrid Approach To Semantic Hashtag Clustering In Social Media, Ali Javed

Graduate College Dissertations and Theses

The uncontrolled usage of hashtags in social media makes them vary a lot in the quality of semantics and the frequency of usage. Such variations pose a challenge to the current approaches which capitalize on either the lexical semantics of a hashtag by using metadata or the contextual semantics of a hashtag by using the texts associated with a hashtag. This thesis presents a hybrid approach to clustering hashtags based on their semantics, designed in two phases. The first phase is a sense-level metadata-based semantic clustering algorithm that has the ability to differentiate among distinct senses of a hashtag as …

A Genetic Programming Approach To Cost-Sensitive Control In Wireless Sensor Networks, Afsoon Yousefi Zowj

Graduate College Dissertations and Theses

In some wireless sensor network applications, multiple sensors can be used to measure the same variable, while differing in their sampling cost, for example in their power requirements. This raises the problem of automatically controlling heterogeneous sensor suites in wireless sensor network applications, in a manner that balances cost and accuracy of sensors. Genetic programming (GP) is applied to this problem, considering two basic approaches. First, a hierarchy of models is constructed, where increasing levels in the hierarchy use sensors of increasing cost. If a model that polls low cost sensors exhibits too much prediction uncertainty, the burden of prediction …